Multi-sensor closed-loop refrigeration control for freight containers

ABSTRACT

Systems and methods can control refrigeration within a refrigerated freight container. Thermal sensor nodes can be positioned within the freight container. Temperature measurements can be wirelessly relayed from the sensor nodes to a gateway associated with the freight container. The received temperature measurements can be aggregated and logged at the gateway. Thermal models of the freight container and associated cargo loads can be established in response to the logged temperature measurements and loading plan for the foreign container. The refrigeration system can be controlled in response to processing the thermal models. The refrigeration system can be controlled to optimize compliance parameters associated with the cargo loads.

RELATED APPLICATIONS

This application claims the benefit under 35 U.S.C. § 120, and is acontinuation, of co-pending application Ser. No. 16/391,868, now U.S.Pat. No. 11,274,879, filed Ap. 23, 2019, which claims priority toProvisional Application 62/661,528, filed Apr. 23, 2018, suchprovisional application also being claimed priority to under 35 U.S.C. §119. These applications are incorporated by reference herein in theirentireties.

BACKGROUND

Freight containers, also known as cargo containers or intermodalcontainers, are standardized shipping containers operable for use acrossdifferent modes of transport such as ships, railroad, or trucking.Refrigerated freight containers are used to transport cargo loads withthermal requirements, such as perishable food or pharmaceuticals. When afault or error in operation of the refrigeration violates the thermalrequirements of the refrigerated cargo loads, the cargo may be wasted.There is a need in the art for freight container closed-looprefrigeration control technology supporting multiple electronic sensors.

SUMMARY

Technologies are described herein for systems and methods to controlrefrigeration within a freight container. Thermal sensor nodes can bepositioned within the freight container. Temperature measurements can bewirelessly relayed from the sensor nodes to a gateway associated withthe freight container. The received temperature measurements can beaggregated and logged at the gateway. Thermal models of the freightcontainer and associated cargo loads can be established in response tothe logged temperature measurements and loading plan for the foreigncontainer. The refrigeration system can be controlled in response toprocessing the thermal models. The refrigeration system can becontrolled to optimize compliance parameters associated with the cargoloads.

It should be appreciated that the described subject matter may beimplemented as an apparatus, a system, an article of manufacture, ormethods/processes associated therewith. These and various other featureswill be apparent from a reading of the following Detailed Descriptionand a review of the associated drawings.

This Summary is provided to introduce a selection of concepts in asimplified form that are further described below in the DetailedDescription. This Summary is not intended to identify key features oressential features of the claimed subject matter, nor is it intendedthat this Summary be used to limit the scope of the claimed subjectmatter. Furthermore, the claimed subject matter is not limited toimplementations that solve any or all disadvantages noted in any part ofthis disclosure.

BRIEF DESCRIPTION OF THE DRAWINGS

FIG. 1 illustrates a multi-sensor, closed-loop refrigeration controlsystem in accordance with one or more embodiments presented herein.

FIG. 2 illustrates modules and communication links within amulti-sensor, closed-loop refrigeration control system according to oneor more embodiments of the technology presented herein.

FIG. 3 is a block flow diagram depicting a method for multi-sensor,closed-loop refrigeration control in accordance with one or moreembodiments of the technology presented herein.

FIG. 4 is a block diagram depicting a computing machine and a module inaccordance with one or more embodiments of the technology presentedherein.

DETAILED DESCRIPTION

The following description is directed to technologies for sensor-drivencontrol of refrigeration systems associated with freight containers.Freight containers may also be known as cargo containers, intermodalcontainers, refrigerated truck trailers, trailers, and various similarterms collectively referred to here as “containers”. Multiple wirelesssensors may be provided within a container. The wireless sensors mayalso be embedded within the cargo carried by the container. Thesesensors can provide data such as detailed environmental measurements anddynamic thermal characteristics of the container. This data can be usedin conjunction with predictive thermal models to better controlrefrigeration of the container. Thermal models may be used inconjunction with a gateway system that allows remote control oftemperature set points. Refrigeration systems can be controlled tomaximize thermal compliance of the container loads, minimize losses,guide load planning, and support other intelligent operations associatedwith refrigerated freight containers.

In the following detailed description, references are made to theaccompanying drawings that form a part hereof, and which are shown byway of illustration specific embodiments or examples. Referring now tothe drawings, in which freight container seal security usingelectromagnetic sensors will be presented.

FIG. 1 illustrates a multi-sensor, closed-loop refrigeration controlsystem according to one or more embodiments of the technology presentedherein. A shipping container 100, also known as a freight container, maybe cooled by a refrigeration system 110. The refrigeration system 110can pump a refrigerated air supply 112 into the shipping container 100.The refrigeration system 110 can draw return air 114 from the shippingcontainer 100. The refrigeration system 110 can process the return air114 by cooling, drying, and/or otherwise controlling humidity. Thus, thereturn air 114 may be transformed into the refrigerated air supply 112to be provided back into the shipping container 100.

Cargo loads 130A-130D may be placed within the shipping container 100for storage and/or transportation. The cargo loads 130A-130D may bereferred to, collectively or in general, as cargo loads 130. The cargoloads 130 may be cooled by the refrigerated air supply 112 to preventdamage or spoiling.

The cargo loads 130 may be discrete items as well as continuous loadshaving similar characteristics such as bulk fresh produce, or otherperishables packaged in similar or identical packaging. Each package mayhave a separate thermodynamic characteristics model, and collectivelymay have a combined model. In this case, the thermal properties of thecargo loads 130 may be best modelled as a collective single load, madeup of similar discrete elements.

Sensor nodes 140 may also be placed within the shipping container 100.Multiple sensor nodes 140 may be distributed around the interior of theshipping container 100. One or more sensor nodes 140 may be positionedwithin, upon, or adjacent to one of the cargo loads 130. One, all, orany number of the cargo loads 130 may be associated with one or moresensor nodes 140. The sensor nodes 140 may be used to measureparameters, such as temperature and humidity, at multiple points withinthe shipping container 100. These multiple points can include pointswithin, upon, or adjacent to respective cargo loads 130.

Measurement from the sensor nodes 140 may be wirelessly relayed to agateway 120. The gateway 120 may comprise a remote-control system forthe container 100 operable to directly, or indirectly, controlrefrigeration functions for the container 100. The gateway 120 may beassociated with the shipping container 100 such that some, or all, ofthe sensor nodes 140 within the shipping container 100 are in wirelesscommunication with the gateway 120.

Temperature values at various points within the shipping container 100can be represented as a scalar field of temperature points. Temperaturesalong any path, plane, or surface within that field may be specified asa temperature gradient. One or more thermal models of the temperaturefield, and or the temperature gradients may be established. Thermalmodels may be based upon the thermal properties of the container itself,and various cargo loads 130 (including packaging), the operation of therefrigeration system 110, the size and position of the various cargoloads 130 (load plan), external temperatures (such as ambient values),known power consumption, and so forth. The thermal models may be used topredict and estimate the temperature at points between or beyond thesensor nodes 140 according to interpolation, extrapolation, and thermalpropagation physics. Thermal propagation physics may involve air flow,temperatures of the refrigerated air supply 112, flow rates of therefrigerated air supply 112, duty cycle of the refrigeration system 110,material composition of the various cargo loads 130, density of thevarious cargo loads 130, materials of the shipping container 100,external temperatures of the shipping container 100, and the actualloading plan which may adversely affect homogeneous air-flow with thecontainer, and so forth. Measurements of the temperatures at pointsgiven by the sensor nodes 140 can drive inputs to the thermal models andalso verify the outputs of the thermal models. The models can establishthree-dimensional temperature matrix at a high spatial resolution.

Each of the cargo loads 130A-130D can have specific parameters. Forexample, pharmacological loads may have a monetary value, a criticalitymetric (e.g., needed vaccines), thermal excursion limits, andsusceptibility to excursion metrics. The thermal exclusion limits mayspecify minimum and maximum safe temperatures for the load. For example,a load may be safe between 0 and 20 degrees centigrade and must be keptwithin that range. Susceptibility to excursion may indicate tolerance ofthe load being exposed to transient temperature exceptions, how large ofexceptions, at what frequency, and for what durations. For example, apharmaceutical load may be specified to keep below 20 degrees centigradebut allow for an excursion to up to 23 degrees only up to one hour induration before the cargo is compromised or damaged.

For collective cargo loads with multiple sensors located in differentgeometries which the load, a thermodynamic model can support maximizingthe overall temperature compliance of the collective cargo load.

Challenges to maintain compliance with cargo loads 130 parameters mayinclude external heating and dissipation, variations in internalcooling, disruption of internal thermal propagation due to load height,variations in cargo load density and thermodynamic properties, and soforth. Ultimately the control system must mitigate these challenges tominimize cost and/or loss impact.

Example parameters associated with food loads may include specificationof mixed or homogeneous loads, freshness parameters (ripening cycles,first picked, first expired, first sold), agricultural product tracking(where harvested, when harvested, how stored, how slaughtered), markingfor tracking (QR codes), USDA cold treatment automation process, and soforth.

The thermal models can be used to control the refrigeration system 110.Best-case control can seek to maximize compliance of an entire load.Best-case control can be maintaining within the thermal excursion limitsof all cargo loads 130A-130D. If the control system cannot make thatgoal and has to sacrifice one or more of the cargo loads 130, knowledgeof the monetary values of the various loads 130 can support decisionsthat minimize monetary loss. Similarly, criticality metrics can be usedto minimize the loss of critical pharmaceutical loads such as vaccinesor products that would take a long time to reproduce and/or risk healthand welfare.

The thermal models can couple to an algorithm for intelligentlycontrolling the refrigeration system. The algorithm can use sensorreadings along with thermal modelling to optimize compliance, predictcompliance, predict alarm conditions, determine critical parameters, andattempt to prevent compliance exceptions through intelligentrefrigeration monitoring and control. The algorithm can generate alarmsbased on predicted temperature profiles. Predicting alarm conditions canallow the algorithm to set refrigeration parameter priorities. Mediationresponses can leverage the timing and critically of alarms orproactively using predicted alarms.

The system can provide a load intelligence application to instruct ashipper on how to pack the cargo loads 130 to maximize compliance orminimize risk of loss. This can include loading order and load heightwithin the container. The system can detect load violations. Forexample, when cargo nearest refrigerated air supply 112 is stacked toohigh and blocking airflow. The system can provide support to the shipperfor establishing the cooling algorithm. The system can predict futuresystem performance and may also provide alerts as appropriate.

System data can be provided in real-time using a Graphical UserInterface. System can support set-up and management of alarms,customizing alarms, notifications and reports that can be sharedsecurely and selectively.

The gateway 120 device can (directly or indirectly) communicate withglobal cellular network partners, report precise locations, and providetwo-way monitoring and control. Cellular or satellite vessel networksmay be leveraged for communications at sea. When there is no connection,the system can store data and transmit it once connectivity is restored.

In addition to temperature, the sensor nodes 140 may support variousother integrated sensors, such as those providing location, humidity,shock, motion, tamper, or light exposure. The sensor nodes 140 cancommunicate from inside the shipping container 100 or from inside withcargo loads 130 themselves.

The system can benefit maintenance by reacting proactively to alarms andother issues thereby reducing maintenance costs. The system can supportpredictive maintenance to reduce component failure and repairrequirements. The system can track warranty expiration dates to performtimely warranty check-ups.

The system can reduce terminal Pre-Trip Inspection (PTI) processes,which are usually performed on a refrigerated container before each use.Performing remote health checks to determining whether repair isnecessary can support improved utilization and reduced repair costs.

The system can automate economy mode setting based on commodity type toreduce energy budgets. The system can maximize energy saving modes. Thesystem can compare energy cost charged against actual usage based on acalculation of power consumption parameters and run-time. The system canidentify which containers are running most efficiently. The system candetermine and monitor best-in-class parameters for refrigeration systemmake and models.

The system can guide in refining various aspects refrigerated containerlogistics and operations. The system can support cross-check of actualset-points, ventilation, and humidity against asset owner's internalsystem. The system can optimize container utilization. The system caneliminate manual monitoring costs and errors. The system can reducemaintenance labor costs. The system can reduce monitoring charge. Thesystem can reduce customer claims. The system can reduce handling costs.The system can identify quality of maintenance and repair on vessels andon land. The system can establish and monitor various makes and modelsof refrigerated containers. The system can manage user profiles for moreefficient operations.

The system can support cargo handling and operations. The system canprovide real-time alarm status on cold treatment shipments. The systemcan support remote change of temperature set point to avoid breach ofprotocol. The system can reduce handling cost. The system can increasecargo shelf life. The system can support quicker clearance throughautomated USDA approvals. The system can provide cargo-level temperaturemonitoring for better USDA and GDP compliance. The system can detectcontainer breach for security. The system can reduce terminal quarantinetime for USDA cold treatment operations. The system can providecustomized real-time data to customers. The system can providecustomized post-trip data to customers.

FIG. 2 illustrates modules and communication links within amulti-sensor, closed-loop refrigeration control system according to oneor more embodiments of the technology presented herein. Sensor nodes 140may be located within a shipping container 100. Each sensor node 140 mayoperate according to one or more sensor modules 230 associated with therespective sensor node 140. Each sensor node 140 may be in wirelesscommunications with a gateway 120. Wireless communications between thesensor node 140 and the gateway 120 may be supported by sensor wirelesschannel 235.

The gateway 120 may operate according to one or more gateway modules240. One or more gateways 120 may be in wireless communications with aserver 210. The server 210 may operate according to one or more servermodules 220. Wireless communications between the gateway 120 and theserver 210 may be supported by gateway wireless channel 215. The server210 may be on ship or fixed, for example at port.

The gateway wireless channel 215 and the sensor wireless channels 235may comprise wireless communication links or networks of wirelesscommunication links. The gateway wireless channel 215 and the sensorwireless channels 235 may employ any of various wireless RF interfacessuch as cellular/mobile (GSM, CDMA, 4G, LTE, 3G), global LoRa, LoRaWAN,GNSS (GPS, Galileo, GLONASS, BeiDou), GPS, Bluetooth, WiFi, satellitelink, WLAN, WiMax, packet radio, software defined radio, and so forth.

The gateway 120, sensor node 140, server 210, or any other systemsassociated with the technology presented herein may be any type ofcomputing machine such as, but not limited to, those discussed in moredetail with respect to FIG. 4. Furthermore, any modules (such as theserver module 220, the sensor module 230, or the gateway module 240)associated with any of these computing machines or any other modules(scripts, web content, software, firmware, or hardware) associated withthe technology presented herein may by any of the modules discussed inmore detail with respect to FIG. 4. The computing machines discussedherein may communicate with one another as well as other computermachines or communication systems over one or more networks orcommunication links such as the gateway wireless channels 215 and/or thesensor wireless channels 235. These communication mechanisms may includeany type of data or communications network including any of the networktechnology discussed with respect to FIG. 4.

FIG. 3 is a block flow diagram depicting a method 300 for multi-sensor,closed-loop refrigeration control in accordance with one or moreembodiments presented herein. According to methods and blocks describedin the embodiments presented herein, and, in alternative embodiments,certain blocks can be performed in a different order, in parallel withone another, omitted entirely, and/or combined between different examplemethods, and/or certain additional blocks can be performed, withoutdeparting from the scope and spirit of the invention. Accordingly, suchalternative embodiments are included in the invention described herein.

In block 310, one or more sensor nodes 140 may be positioned in andaround cargo loads 130 within a shipping container 100. The sensor nodes140 may be distributed around the interior of the shipping container100. One or more sensor nodes 140 may be positioned within, upon, oradjacent to one of the cargo loads 130. The sensor nodes 140 may be usedto measure parameters, such as temperature and humidity, at multiplepoints within the shipping container 100.

In block 320, measurements from the sensor nodes 140 may be wirelesslyrelayed to a gateway 120. The gateway 120 may comprise a remote-controlsystem for the container 100 operable to directly, or indirectly,control refrigeration functions for the container 100. The gateway 120may be associated with the shipping container 100 such that some, orall, of the sensor nodes 140 within the shipping container 100 are inwireless communication with the gateway 120.

In block 330, received measurements may be aggregated and/or logged byor at the gateway.

In block 340, thermal models may be based upon the thermal properties ofthe container itself, and various cargo loads 130, the operation of therefrigeration system 110, the size and position of the various cargoloads 130, external temperatures, known power consumption, and so forth.The thermal models may be used to predict and estimate the temperatureat points between or beyond the sensor nodes 140 according tointerpolation, extrapolation, and thermal propagation physics. Thermalpropagation physics may be computed from air flow, temperatures of therefrigerated air supply 112, flow rates of the refrigerated air supply112, duty cycle of the refrigeration system 110, material composition ofthe various cargo loads 130, density of the various cargo loads 130,materials of the shipping container 100, external temperatures of theshipping container 100, the loading plan, and so forth. The thermalmodels can establish a three-dimensional temperature matrix at a highspatial resolution. The thermal models may include specific physicalparameters associated with each of the cargo loads 130. For example,pharmacological loads may have a monetary value, a criticality metric(e.g., needed vaccines), thermal excursion limits, and susceptibility toexcursion metrics. The thermal exclusion limits may specify minimum andmaximum safe temperatures for the load. For example, a load may be safebetween 0 and 20 degrees centigrade and must be kept within that range.

In block 350, thermal models can be used to automatically andintelligently control the refrigeration system 110. Control may beestablished over refrigeration temperature set points, refrigerationcycles, fan power, humidity control, and so forth.

In block 360, control of the refrigeration system can supportmaintaining load compliance. In best-case scenarios, the control canseek to maximize compliance of an entire load by maintainingtemperatures (or other parameters) within the tolerance limits of allcargo loads 130. If the control system cannot make that goal, it may beforced to sacrifice one or more of the cargo loads 130. Analysis of themonetary values and criticality of the various loads 130 can supportdecisions that minimize loss while minimizing risks to health, welfare,or other human needs.

Example compliance parameters associated with food loads may includespecification of mixed or homogeneous loads, freshness parameters(ripening cycles, first picked, first expired, first sold), agriculturalproduct tracking (where harvested, when harvested, how stored, howslaughtered), marking for tracking (QR codes), USDA cold treatmentautomation process, and so forth.

In block 370, the logged measurements may be transmitted from thegateway 120 to the server 210. The transferred information may alsoinclude the results of modelling and analysis. The information may betransmitted by wireless communications between the gateway 120 and theserver 210, which may be supported by gateway wireless channel 215. Theserver 210 may be on ship or fixed, for example at port. The gateway 120can communicate, directly or indirectly, with the server 210 using aglobal cellular network, or other wireless mechanisms as presentedherein. When there is no connection, the gateway 120 can store data andtransmit it once connectivity is restored.

In block 380, operations reports and alerts associated with therefrigerated container 100 may be generated. The generated reports maybe uploaded via the server 210 or other communications channel. Systemdata can be provided in real-time using a Graphical User Interface. Thesystem can support set-up and management of alarms, customizing alarms,notifications and reports that can be shared securely and selectively.The system can provide support to the shipper for establishing thecooling algorithm. The system can predict future system performance andmay also provide alerts as appropriate.

In block 390, load planning and inspections may be supported byinformation collection and analysis associated with the gateway 120 andthe server 210. Load planning intelligence can be provided with respectto size and position of the various cargo loads 130. The loan plan caninstruct a shipper on how to pack the cargo loads 130 to maximizecompliance or minimize risk of loss. This can include loading order andload height within the container. The system can detect load violations.For example, when cargo nearest refrigerated air supply 112 is stackedtoo high and blocking airflow.

The system can reduce terminal Pre-Trip Inspection (PTI) processes,which are usually performed on a refrigerated container before each use.Performing remote health checks to determining whether repair isnecessary can support improved utilization and reduced repair costs. Thesystem can also provide real-time alarm status on cold treatmentshipments. The system can support remote change of temperature set pointto avoid breach of protocol. The system can reduce handling cost. Thesystem can increase cargo shelf life. The system can support quickerclearance through automated USDA approvals. The system can providecargo-level temperature monitoring for better USDA and GDP compliance.The system can detect container breach for security. The system canreduce terminal quarantine time for USDA cold treatment operations. Thesystem can provide customized real-time data to customers. The systemcan provide customized post-trip data to customers.

FIG. 4 depicts a computing machine 2000 and a module 2050 in accordancewith one or more embodiments presented herein. The computing machine2000 may correspond to any of the various computers, servers, mobiledevices, embedded systems, or computing systems presented herein. Themodule 2050 may comprise one or more hardware or software elementsconfigured to facilitate the computing machine 2000 in performing thevarious methods and processing functions presented herein. The computingmachine 2000 may include various internal or attached components such asa processor 2010, system bus 2020, system memory 2030, storage media2040, input/output interface 2060, and a network interface 2070 forcommunicating with a network 2080.

The computing machine 2000 may be implemented as a conventional computersystem, an embedded controller, a laptop, a server, a mobile device, asmartphone, a set-top box, a kiosk, a vehicular information system, onemore processors associated with a television, a customized machine, anyother hardware platform, or any combination or multiplicity thereof. Thecomputing machine 2000 may be a distributed system configured tofunction using multiple computing machines interconnected via a datanetwork or bus system.

The processor 2010 may be configured to execute code or instructions toperform the operations and functionality described herein, managerequest flow and address mappings, and to perform calculations andgenerate commands. The processor 2010 may be configured to monitor andcontrol the operation of the components in the computing machine 2000.The processor 2010 may be a a processor core, a multiprocessor, areconfigurable processor, a microcontroller, a digital signal processor(“DSP”), an application specific integrated circuit (“ASIC”), a graphicsprocessing unit (“GPU”), a field programmable gate array (“FPGA”), aprogrammable logic device (“PLD”), a controller, a state machine, gatedlogic, discrete hardware components, any other processing unit, or anycombination or multiplicity thereof. The processor 2010 may be a singleprocessing unit, multiple processing units, a single processing core,multiple processing cores, special purpose processing cores,co-processors, or any combination thereof. According to certainembodiments, the processor 2010 along with other components of thecomputing machine 2000 may be a virtualized computing machine executingwithin one or more other computing machines.

The system memory 2030 may include non-volatile memories such asread-only memory (“ROM”), programmable read-only memory (“PROM”),erasable programmable read-only memory (“EPROM”), flash memory, or anyother device capable of storing program instructions or data with orwithout applied power. The system memory 2030 also may include volatilememories, such as random access memory (“RAM”), static random accessmemory (“SRAM”), dynamic random access memory (“DRAM”), and synchronousdynamic random access memory (“SDRAM”). Other types of RAM also may beused to implement the system memory 2030. The system memory 2030 may beimplemented using a single memory module or multiple memory modules.While the system memory 2030 is depicted as being part of the computingmachine 2000, one skilled in the art will recognize that the systemmemory 2030 may be separate from the computing machine 2000 withoutdeparting from the scope of the subject technology. It should also beappreciated that the system memory 2030 may include, or operate inconjunction with, a non-volatile storage device such as the storagemedia 2040.

The storage media 2040 may include a hard disk, a floppy disk, a compactdisc read only memory (“CD-ROM”), a digital versatile disc (“DVD”), aBlu-ray disc, a magnetic tape, a flash memory, other non-volatile memorydevice, a solid-state drive (“SSD”), any magnetic storage device, anyoptical storage device, any electrical storage device, any semiconductorstorage device, any physical-based storage device, any other datastorage device, or any combination or multiplicity thereof. The storagemedia 2040 may store one or more operating systems, application programsand program modules such as module 2050, data, or any other information.The storage media 2040 may be part of, or connected to, the computingmachine 2000. The storage media 2040 may also be part of one or moreother computing machines that are in communication with the computingmachine 2000 such as servers, database servers, cloud storage, networkattached storage, and so forth.

The module 2050 may comprise one or more hardware or software elementsconfigured to facilitate the computing machine 2000 with performing thevarious methods and processing functions presented herein. The module2050 may include one or more sequences of instructions stored assoftware or firmware in association with the system memory 2030, thestorage media 2040, or both. The storage media 2040 may thereforerepresent examples of machine or computer readable media on whichinstructions or code may be stored for execution by the processor 2010.Machine or computer readable media may generally refer to any medium ormedia used to provide instructions to the processor 2010. Such machineor computer readable media associated with the module 2050 may comprisea computer software product. It should be appreciated that a computersoftware product comprising the module 2050 may also be associated withone or more processes or methods for delivering the module 2050 to thecomputing machine 2000 via the network 2080, any signal-bearing medium,or any other communication or delivery technology. The module 2050 mayalso comprise hardware circuits or information for configuring hardwarecircuits such as microcode or configuration information for an FPGA orother PLD.

The input/output (“I/O”) interface 2060 may be configured to couple toone or more external devices, to receive data from the one or moreexternal devices, and to send data to the one or more external devices.Such external devices along with the various internal devices may alsobe known as peripheral devices. The I/O interface 2060 may include bothelectrical and physical connections for operably coupling the variousperipheral devices to the computing machine 2000 or the processor 2010.The I/O interface 2060 may be configured to communicate data, addresses,and control signals between the peripheral devices, the computingmachine 2000, or the processor 2010. The I/O interface 2060 may beconfigured to implement any standard interface, such as small computersystem interface (“SCSI”), serial-attached SCSI (“SAS”), fiber channel,peripheral component interconnect (“PCI”), PCI express (PCIe), serialbus, parallel bus, advanced technology attachment (“ATA”), serial ATA(“SATA”), universal serial bus (“USB”), Thunderbolt, FireWire, variousvideo buses, and the like. The I/O interface 2060 may be configured toimplement only one interface or bus technology. Alternatively, the I/Ointerface 2060 may be configured to implement multiple interfaces or bustechnologies. The I/O interface 2060 may be configured as part of, allof, or to operate in conjunction with, the system bus 2020. The I/Ointerface 2060 may include one or more buffers for bufferingtransmissions between one or more external devices, internal devices,the computing machine 2000, or the processor 2010.

The I/O interface 2060 may couple the computing machine 2000 to variousinput devices including mice, touchscreens, scanners, biometric readers,electronic digitizers, sensors, receivers, touchpads, trackballs,cameras, microphones, keyboards, any other pointing devices, or anycombinations thereof. The I/O interface 2060 may couple the computingmachine 2000 to various output devices including video displays,speakers, printers, projectors, tactile feedback devices, automationcontrol, robotic components, actuators, motors, fans, solenoids, valves,pumps, transmitters, signal emitters, lights, and so forth.

The computing machine 2000 may operate in a networked environment usinglogical connections through the network interface 2070 to one or moreother systems or computing machines across the network 2080. The network2080 may include wide area networks (“WAN”), local area networks(“LAN”), intranets, the Internet, wireless access networks, wirednetworks, mobile networks, telephone networks, optical networks, orcombinations thereof. The network 2080 may be packet switched, circuitswitched, of any topology, and may use any communication protocol.Communication links within the network 2080 may involve various digitalor an analog communication media such as fiber optic cables, free-spaceoptics, waveguides, electrical conductors, wireless links, antennas,radio-frequency communications, and so forth.

The processor 2010 may be connected to the other elements of thecomputing machine 2000 or the various peripherals discussed hereinthrough the system bus 2020. It should be appreciated that the systembus 2020 may be within the processor 2010, outside the processor 2010,or both. According to some embodiments, any of the processor 2010, theother elements of the computing machine 2000, or the various peripheralsdiscussed herein may be integrated into a single device such as a systemon chip (“SOC”), system on package (“SOP”), or ASIC device.

In situations in which the systems discussed here collect personalinformation about users, or may make use of personal information, theusers may be provided with an opportunity to control whether programs orfeatures collect user information (e.g., information about a user'ssocial network, social actions or activities, profession, a user'spreferences, or a user's current location), or to control whether and/orhow to receive content from the content server that may be more relevantto the user. In addition, certain data may be treated in one or moreways before it is stored or used, so that personally identifiableinformation is removed. For example, a user's identity may be treated sothat no personally identifiable information can be determined for theuser, or a user's geographic location may be generalized where locationinformation is obtained (such as to a city, ZIP code, or state level),so that a particular location of a user cannot be determined. Thus, theuser may have control over how information is collected about the userand used by a content server.

One or more aspects of embodiments may comprise a computer program thatembodies the functions described and illustrated herein, wherein thecomputer program is implemented in a computer system that comprisesinstructions stored in a machine-readable medium and a processor thatexecutes the instructions. However, it should be apparent that therecould be many different ways of implementing embodiments in computerprogramming, and the invention should not be construed as limited to anyone set of computer program instructions. Further, a skilled programmerwould be able to write such a computer program to implement anembodiment of the disclosed invention based on the appended flow chartsand associated description in the application text. Therefore,disclosure of a particular set of program code instructions is notconsidered necessary for an adequate understanding of how to make anduse the invention. Further, those skilled in the art will appreciatethat one or more aspects of the invention described herein may beperformed by hardware, software, or a combination thereof, as may beembodied in one or more computing systems. Moreover, any reference to anact being performed by a computer should not be construed as beingperformed by a single computer as more than one computer may perform theact.

The example embodiments described herein can be used with computerhardware and software that perform the methods and processing functionsdescribed previously. The systems, methods, and procedures describedherein can be embodied in a programmable computer, computer-executablesoftware, or digital circuitry. The software can be stored oncomputer-readable media. For example, computer-readable media caninclude a floppy disk, RAM, ROM, hard disk, removable media, flashmemory, memory stick, optical media, magneto-optical media, CD-ROM, etc.Digital circuitry can include integrated circuits, gate arrays, buildingblock logic, field programmable gate arrays (“FPGA”), etc.

Based on the foregoing, it should be appreciated that technologies forwireless security associated with freight container seals are presentedherein. Although the subject matter presented herein has been describedin language specific to various example embodiments, it is to beunderstood that the invention disclosed herein is not necessarilylimited to the specific features, materials, dimensions, or structuresdescribed herein. Rather, the specific features, materials, dimensions,and structures are disclosed as example forms of implementation. Thesubject matter described above is provided by way of illustration onlyand should not be construed as limiting. Various modifications,combinations, and changes may be made to the subject matter describedherein without following the example embodiments and applicationsillustrated and described, and without departing from the true spiritand scope of the present invention.

1. A method for refrigeration control in a freight container in activetransit, the method comprising: wirelessly receiving, at a gateway,measurements from a first sensor node and a second sensor node, wherein,the measurements include at least one of temperature, humidity, andlight detected by the sensor nodes, and the first sensor node is storedinside of a cargo load stored inside of the freight container, and thesecond sensor node is stored outside of the cargo load and inside of thefreight container; and controlling a refrigeration system in the freightcontainer based on the measurements to preserve cargo stored inside ofthe cargo load.
 2. The method of claim 1, wherein the wirelesslyreceiving uses at least one of a satellite network, a cellular network,and Long Range (LoRa) modulation standard.
 3. The method of claim 1,wherein the gateway is co-located with the freight container, the methodfurther comprising: wirelessly transmitting, from the gateway to aserver, the measurements, wherein the server is remote from the freightcontainer and not in transit, and wherein the wirelessly transmittinguses at least one of a satellite network, a cellular network, and LongRange (LoRa) modulation standard.
 4. The method of claim 1, wherein thecontrolling includes inputting the measurements into a predictivethermal model to estimate physical parameters of the cargo between thesensor nodes.
 5. The method of claim 4, further comprising: establishingthe predictive thermal model from the measurements over time andoperation of the refrigeration system.
 6. The method of claim 5, whereinthe establishing further includes establishing the predictive thermalmodel from thermal properties of the freight container and thermalproperties of the cargo load.
 7. The method of claim 4, wherein thepredictive thermal model is a temperature field within the freightcontainer and cargo load.
 8. The method of claim 1, wherein the freightcontainer contains, a plurality of the cargo loads each with a firstsensor node stored inside, and a plurality of the second sensor nodesoutside the cargo loads inside the freight container, wherein themeasurements include measurements from all of the first and all of thesecond sensor nodes.
 9. The method of claim 8, wherein the controllingincludes allowing one of the cargo loads to exceed a temperature limitand sacrificing the one of the cargo loads to preserve temperature limitcompliance of another of the cargo loads.
 10. The method of claim 9,wherein the one of the cargo loads sacrificed has a lower monetary valueor importance value than the another of the cargo loads.
 11. The methodof claim 1, wherein, the freight container is an intermodal containerstandardized for operation in shipping, railroad, and trucking, therefrigeration system is a closed-loop refrigeration system intaking airfrom and inputting cooled air into the freight container, and thewirelessly receiving uses an electromagnetic interface that passesthrough the cargo loads and the freight container.
 12. A refrigerationcontrol system for use in a freight container in active transit, thesystem comprising: a first sensor node configured to store inside of acargo load stored inside of the freight container; a second sensor nodeconfigured to store outside of the cargo load and inside of the freightcontainer, wherein the first and the second sensor nodes measure atleast one of temperature, humidity, and light; and a gateway associatedwith the freight container not inside any cargo load and configured to,wirelessly receive the measurements from the first sensor node and thesecond sensor node, and control a refrigeration system in the freightcontainer based on the measurements to preserve cargo stored inside ofthe cargo load.
 13. The system of claim 12, wherein the gateway isconfigured to wirelessly communicate on at least one of a satellitenetwork, a cellular network, and Long Range (LoRa) modulation standard.14. The system of claim 12, further comprising: the refrigerationsystem, wherein the gateway and the refrigeration system are co-locatedwith the freight container, wherein the gateway is further configured towirelessly transmit, to a server, the measurements, wherein the serveris remote from the freight container and not in transit, and wherein thewirelessly transmitting uses at least one of a satellite network, acellular network, and Long Range (LoRa) modulation standard.
 15. Thesystem of claim 14, further comprising: the freight container, whereinthe freight container is an intermodal container standardized foroperation in shipping, railroad, and trucking, and wherein therefrigeration system is a closed-loop refrigeration system intaking airfrom and inputting cooled air into the freight container.
 16. The systemof claim 12, wherein the gateway is further configured to inputting themeasurements into a predictive thermal model to estimate physicalparameters of the cargo between the sensor nodes.
 17. The system ofclaim 16, wherein the gateway is further configured to establish thepredictive thermal model from the measurements over time and operationof the refrigeration system.
 18. The system of claim 17, wherein thegateway is further configured to establish the predictive thermal modelfrom thermal properties of the freight container and thermal propertiesof the cargo load, wherein the predictive thermal model is a temperaturefield within the freight container and cargo load.
 19. The system ofclaim 12, further comprising; a plurality of the first sensor nodes eachconfigured to store inside of a cargo load inside the freight container;and a plurality of the second sensor nodes each configured to storeoutside the cargo loads inside the freight container, wherein themeasurements include measurements from all of the first and all of thesecond sensor nodes.
 20. The system of claim 12, wherein the gateway isfurther configured to allow one of the cargo loads to exceed atemperature limit and sacrifice the one of the cargo loads to preservetemperature limit compliance of another of the cargo loads having ahigher monetary value or importance value than the one of the cargoloads sacrificed.